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Strobe sequence design for haplotype assembly

Overview of attention for article published in BMC Bioinformatics, February 2011
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2 tweeters

Citations

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17 Dimensions

Readers on

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60 Mendeley
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2 CiteULike

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Title
Strobe sequence design for haplotype assembly
Published in
BMC Bioinformatics, February 2011
DOI 10.1186/1471-2105-12-s1-s24
Pubmed ID
21342554
Authors

Christine Lo, Ali Bashir, Vikas Bansal, Vineet Bafna

Abstract

Humans are diploid, carrying two copies of each chromosome, one from each parent. Separating the paternal and maternal chromosomes is an important component of genetic analyses such as determining genetic association, inferring evolutionary scenarios, computing recombination rates, and detecting cis-regulatory events. As the pair of chromosomes are mostly identical to each other, linking together of alleles at heterozygous sites is sufficient to phase, or separate the two chromosomes. In Haplotype Assembly, the linking is done by sequenced fragments that overlap two heterozygous sites. While there has been a lot of research on correcting errors to achieve accurate haplotypes via assembly, relatively little work has been done on designing sequencing experiments to get long haplotypes. Here, we describe the different design parameters that can be adjusted with next generation and upcoming sequencing technologies, and study the impact of design choice on the length of the haplotype.

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Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
France 2 3%
Italy 1 2%
Norway 1 2%
United Kingdom 1 2%
China 1 2%
Germany 1 2%
Unknown 51 85%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 30%
Researcher 16 27%
Other 6 10%
Professor > Associate Professor 5 8%
Student > Master 4 7%
Other 9 15%
Unknown 2 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 36 60%
Computer Science 12 20%
Biochemistry, Genetics and Molecular Biology 6 10%
Mathematics 1 2%
Social Sciences 1 2%
Other 1 2%
Unknown 3 5%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 January 2021.
All research outputs
#13,136,366
of 17,125,476 outputs
Outputs from BMC Bioinformatics
#4,828
of 6,086 outputs
Outputs of similar age
#12,363,867
of 15,968,251 outputs
Outputs of similar age from BMC Bioinformatics
#4,828
of 6,085 outputs
Altmetric has tracked 17,125,476 research outputs across all sources so far. This one is in the 20th percentile – i.e., 20% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,086 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one is in the 15th percentile – i.e., 15% of its peers scored the same or lower than it.
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